In the context of the CAP theorem, which stands for Consistency, Availability, and Partition Tolerance, a distributed system can simultaneously provide only two of these three guarantees. Therefore, when one says that CA (Consistency and Availability) is acceptable, it implies that the system can forgo Partition Tolerance, meaning it operates under the assumption of a robust network where partitions are either rare or can be quickly resolved.

This scenario is feasible in environments where network partitions are extremely unlikely due to strong infrastructure and where consistently accurate data is more vital than the system remaining available during partition events. This might happen in intranets or local high-speed networks, where the control over infrastructure minimizes the risk of partitions. In these situations, the system prioritizes keeping all nodes consistent with the latest data and ensuring high availability, accepting that it might not handle network splits gracefully. This approach suits applications where data integrity is prioritized over availability during network failures, such as financial services, which demand strong consistency to avoid discrepancies in account balances.